\docType{methods}
\name{dlmm-methods}
\alias{dlmm-methods}
\alias{dynef,dlmm-method}
\alias{fixef}
\alias{fixef,dlmm-method}
\alias{refit}
\alias{refit,dlmm,missing-method}
\alias{show}
\alias{show,dlmm-method}
\alias{summary}
\alias{summary,dlmm-method}
\alias{VarCorr}
\alias{VarCorr,dlmm-method}
\title{Methods defined for the \code{dlmm} class}
\arguments{
  \item{object}{an object of class \code{"dlmm"}}

  \item{object}{an object of class \code{"dlmm"}}

  \item{type}{a character string indicating whether the
  median or the mean should be used}

  \item{sd}{whether standard deviations should be computed.
  If so, they are stored in the \code{"sd"} attribute of
  the returned result.}

  \item{quantile}{a numeric vector of probabilities with
  values in \code{[0,1]}.  These are used to compute the
  empirical quantiles.}

  \item{...}{not used}

  \item{newrep}{not used}
}
\description{
  \bold{\code{dynef}}: generic function for extracting
  dynamic effects

  \bold{\code{fixef}}: extract fixed effects

  \bold{\code{VarCorr}}: extract the variance component
  estimation.

  \code{summary}: produce summary report for the fitted
  model.

  \code{show}: the default print (show) method for a dlmm
  object.

  \bold{\code{refit}}: refit a \code{dlmm} object with
  modified structure. This is useful when the desired model
  is not a standard one supported by the current
  functionality. The user can use the \code{dlmm_bugs}
  function with argument \code{do.fit = FALSE} to set up
  the basic model structure. The user then needs to modify
  the bugs script stored in \code{model.file}, the
  underlying \code{data}, or the initial values
  \code{inits} to accommodate the desired model. A call of
  \code{refit} then fits the model with the new setup.
}

